Statistical analysis involves aggregating and interpreting data. Modern computing devices are capable of performing such analysis with ever-increasing speed and efficiency. Software statistical analysis tools now have access to a wealth of available data. Everything from financial information and demographic data to user behavior and interests is aggregated by pervasive networks of data centers and devices. Mathematicians and engineers struggle to draw meaningful conclusions from this information.
As the abundance and availability of data has increased dramatically, so too has the complexity of the user experience. Users are expected to learn new software and to perform complex tasks with varying amounts of guidance. Ironically, software developers have created vast libraries of help information and resources in order to assist the user. Navigating such resources in search of specific information can be a daunting task. As a result, many problems in the usability and design of software relate to what is commonly referred to as “information overload.”
For example, in the area of tax preparation, existing software tools are capable of maintaining compliance with ever-changing government regulations and requirements. This causes uncertainty in the user experience. Users must learn and adapt to these changes in the program, while the delivery of content to the user remains somewhat static.